Overview
There are several available tools for this purpose and one of the most used is Stable Diffusion developed by Stability AI. It is Open Source, has great usability, and speed, and can generate high-quality images. As it is open source, developers have created many extensions that can generate an infinite variety of images in the most different styles. In this course, you will learn everything you need to know to create new images using Stable Diffusion and Python programming language.
Why this
course?
In this course, you will learn:
- Understand the basics of Stable Diffusion to create new images
- Learn how to use Stable Diffusion parameters to get different results
- Create images using other models provided by the Open-Source community
- Learn about Prompt Engineering to choose the best keywords to generate the best images
- How to use negative prompts to indicate what should not appear in the images
- Use fine-tuning to create your custom model to generate your images
- Send initial images to condition image generation
- Use inpainting to edit images, remove unwanted elements, or swap objects
Curriculum
- Stable Diffusion - intuition 1
- Stable Diffusion - intuition 2
- Stable Diffusion - intuition 3
- Stable Diffusion - intuition 4
- Stable Diffusion - limitations of use
- Installing the libraries
- Prompts - intuition
- Generating the first image
- Generating multiple images
- Parameters - seed
- Parameters - inference step
- Parameters - guidance scale
- Negative prompts - intuition
- Negative prompts - implementation
- Other models - intuition
- Other models - implementation
- Specific styles
- Changing the scheduler
- Preparing the environment
- Subject/object, action/location, and type
- Style, colors, and artist
- Resolution, site, and other attributes
- Negative prompts
- Stable Diffusion v2
- Generating art and photographs
- Generating landscapes and 3D images
- Generating drawings and architectures
- Custom models
- Fine-tuning with Dream Booth – intuition
- Preparing the environment
- Training 1
- Training 2
- Generating the images
- Improving the results
- Preparing the environment
- Generating the image
- Strength parameter
- Other image styles
- Other models
- Adding elements
- Preparing the environment
- Exchanging classes 1
- Exchanging classes 2
- Preparing the environment
- Generating images using edges 1
- Generating images using edges 2
- Generating images using poses 1
- Generating images using poses 2
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Prerequisites
Programming logic and Python basics are desirable but not required
FAQs
Generative AI is a subset of AI that focuses on understanding patterns and structure in data and then using that to create more data like it.
Until now, machines couldn’t exhibit behavior that was indistinguishable from human responses. Generative AI has made that possible. In a world that operates on the principle of ‘Survival of the Fittest’, embracing Generative AI could be the edge you need to boost your productivity, improve operations, be more reliable and consistent, and do so much more.
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Yes, absolutely! The Introduction to Stable Diffusion for Developers & Designers online course is a virtual, instructor-led program so you can enroll and learn from anywhere.
This course is designed to be highly hands-on for all learners. Roughly 70% of this course would be hands-on practical training while 30% would be theoretical studies.
Yes! There will be a pre- and post-assessment for every module during this Stable Diffusion online training course.
